Distributed Estimation of a Layered Architecture for Collaborative Air-Ground Target Geolocation in Outdoor Environments

Lele Zhang, Feng Gao, Fang Deng, Lele Xi, Jie Chen

Abstract: To solve the problem of collaborative air–ground target search and localization in large outdoor environments, we adopt a distributed layered architecture and propose a corresponding distributed estimation algorithm, which can produce accurate estimates of interested target position. The air–ground system consists of a single unmanned aerial vehicle (UAV) and several ground platforms. First, for the distributed layered architecture, this article develops unbalanced simple convex combination algorithm using one-shot measurements from the single UAV and all ground platforms to generate global estimates of the stationary target state. The novelty of the proposed algorithm is that it considers the differences in sensor capabilities between the aerial and ground platforms. Then, performance analysis is described to show that the proposed algorithm is obviously superior to the traditional existing convex combination algorithms. Finally, the efficacy of this algorithm is further demonstrated by the simulation experiments and actual geolocation tests.